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\begin{cabstract}

在虚拟现实环境中对复杂的自然现象进行模拟和重现一直是一个非常吸引人同时又具有难度的问题。对动态的烟、雾等无定形物参与介质的建模研究工作主要是基于物理模拟的方法。近年来，基于图像的方法由于具有真实度高、细节保存完整等优点，成为了计算机图形学和视觉领域的研究热点。为了在虚拟环境中逼真的再现动态非均匀参与介质的视觉特征，本文在国家自然科学基金项目“真实物体表面属性建模与绘制技术研究(60773153)”资助下，研究基于图像的方法来对动态参与介质进行逼真建模，并取得了如下成果：

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设计和搭建了一套动态参与介质数据采集系统BH\_SmokeDome。根据动态参与介质自身的光学特征和成像特点，安装了可同步触发的高速相机、光源等设备，并开发了一系列软件工具用于完成采集任务和数据处理工作。

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提出了一种基于图像的动态非均匀参与介质体数据重构算法。采用逆向绘制的方法，以模拟成像过程进行绘制得到的图像与采集得到的图像之间的差别作为优化的目标函数，将参与介质体数据重构问题转化为大量未知数的非线性优化问题。针对这一问题的求解，提出了一种GPU上的目标函数值和梯度值计算算法，实现了CPU、GPU协同工作的优化算法。针对多帧数据的恢复，提出了一种利用时间相关性来初始化后继帧的初始化算法来提高后继帧的数值优化效率。

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实现了一种基于改进的ray marching技术的单散射参与介质绘制技术。结合BH\_SmokeDome数据采集系统内的光照特点，对传输方程做了适当简化，得到合理简化后的成像模型。并利用OpenGL的着色语言和alpha混合功能实现了简化后的成像模型的绘制算法。此外，针对体数据优化重构算法中的梯度计算的并行性特点，实现了一种体数据并行扰动的绘制算法，与GPU端的函数梯度计算程序相结合，提高了问题求解的并行性。

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基于本文研究的算法，实现了动态参与介质建模工具DPMM。该工具实现了建模和绘制两个部分，具有交互功能，能够控制建模过程和展示建模结果。

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\end{cabstract}

\ckeywords{动态参与介质，多相机系统，基于图像建模，逆向绘制，GPU高性能计算}


\begin{eabstract} 

Visual simulation of complex natural phenomena in Virtual Reality (VR) applications is always a fascinating and challenging problem. In recent years, image-based methods for modeling real world objects and scenes have been an active field of research in both computer vision and graphics. While most of these work focuses on the modeling of rigid or opaque objects, very little work falls in the category of modeling dynamic participating media. Realistic modeling of dynamic participating media is important to a number of VR applications, because the presence of participating media in the virtual scene significantly improve the sense of reality and immersion.

Motivated by realistically reproducing natural phenomena of dynamic participating media in virtual environment, this thesis, which is supported by the National Natural Science Foundation of China project "Research on modeling and rendering of real-world objects appearance (NO. 60773153)", focus on image-based techniques for participating media modeling. The main achievements are listed below.

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We design and build the BH\_SmokeDome system for multi-view video data capture of dynamic participating media. Based on the former BH\_DOME system which is aimed to capture reflectance attributes for solid objects, we set up new capture devices to resolve the optical and imaging characteristics of dynamic participating media. We also developed a series of software tools to assist the capture tasks and data preprocessing. 

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We present an image-based method for reconstructing volume data of dynamic inhomogeneous participating media. In an inverse rendering manner, we solve for the volumetric density data of participating media by converting it into a large-scale non-linear optimization problem which minimizes the difference between rendered result's images and captured ones. We implemented a CPU/GPU combined method for the numerical optimization process and hereby propesed a method for objective function evaluation and gradients computation on the GPUs. For multi-frame input data, we introduce an approach to improve the efficiency of time-varying volumetric reconstructing by exploiting temporal-coherence.

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We implement a modified ray marching method to rendering single scattering participating media. We simplified it by excluding light effects that are impossible in the BH\_SmokeDome system. We substantiate the simplified transport using fragment shader and alpha blending function of OpenGL. What is more, we implemented a parallel multi-voxel perturbation rendering method, which is combined with the gradients evaluating program on the GPU to enhance the parallelism.

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Based on the research work above, we designed and implemented the participating media modeling tool. The tool consists of modeling and rendering components. The modeling component enables conveniently configure the input parameters, such as data location, camera parameter matrices and media properties; The rendering component provides interactive and intuitive exhibition of the modeling results, enabling arbitrary modification of viewpoint and light position.

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\end{eabstract}

\ekeywords{dynamic participating media, multi-camera system, image-based modeling, inverse rendering, GPU high performance computing}
